1. Field of the Invention
The present invention relates to image processing. More specifically, the present invention relates to automatic target recognition.
2. Description of the Related Art
Radar target detection and identification has been useful in many applications such as military surveillance, reconnaissance, and combat missions. The detection and identification of targets can provide real-time assessment of the number and locations of the targets, or objects of interest. One method of target detection and identification involves acquiring an image of a target scene using synthetic aperture radar (SAR) and then processing the image to extract the features of any targets and match the features to a database for identification.
Synthetic aperture radar systems acquire an image of a scene by coherently combining return signals from a plurality of sequentially transmitted radar pulses from a relatively small radar antenna on a moving platform. The plurality of returns generated by the transmitted pulses along the known path of the platform make up an array length. Across the array length, the amplitude and phase information returned from each of the pulses for each of several range bins is preserved, forming a SAR image having an image quality comparable to that obtained by a larger antenna (corresponding approximately to the synthetic length traveled by the antenna during the acquisition of the image).
An automatic target recognition (ATR) system processes a SAR image to detect and identify targets in the image. An ATR system typically includes an automatic target cuer (ATC) and a matcher. The ATC processes the SAR image to detect targets of interest, obtaining the location, length, width, and orientation of targets in the image. Target chips, which are small portions of the original SAR image, where each chip typically contains one target, are then sent to the matcher for identification. The matcher processes each target chip and compares it to various target classes in a stored database to identify the target.
Several matcher algorithms, including the algorithm used by the Real-Time Moving and Stationary Target Acquisition and Recognition (RT-MSTAR) system, use model-based target recognition to identify targets. Model-based recognition typically uses models of the targets to synthesize expected SAR images for each target class under a variety of viewing conditions (such as target orientation relative to the radar) and then searches for the target type/orientation combination that maximizes some match metric between the synthesized image and the observed image. These types of systems perform relatively well and are particularly robust with respect to target orientation and viewing conditions. However, these systems still generate false alarm rates (incorrect identifications) that can be higher than desirable if not used in an optimal manner.
Hence, a need exists in the art for an improved automatic target recognition system that is more accurate than prior approaches.